Using data mining to study the impact of topology characteristics on the performance of wireless mesh networks

This paper quantifies the impact of topological characteristics on the performance of single radio multichannel IEEE802.11 mesh networks. Topological characteristics are the number of nodes per subnetwork, the hop count, the neighbor node density, the hidden nodes, the number of nodes in the neighbo...

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Bibliographic Details
Main Author: Calçada, Tânia (author)
Other Authors: Cortez, Paulo (author), Ricardo, Manuel (author)
Format: conferencePaper
Language:eng
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/1822/19888
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/19888
Description
Summary:This paper quantifies the impact of topological characteristics on the performance of single radio multichannel IEEE802.11 mesh networks. Topological characteristics are the number of nodes per subnetwork, the hop count, the neighbor node density, the hidden nodes, the number of nodes in the neighborhood of the gateway, and the hidden nodes in the neighborhood of the gateway. Network performance metrics are throughput, fairness and delay. The data mining Support Vector Machine (SVM) model was used to extract the relationships between the network topology metrics and the network per- formance metrics based on data results obtained through ns- 2 simulation of random networks. The results obtained can be used as a basis to design channel assignment algorithms or to aid the deployment and management of single radio wireless mesh networks.